Remote Sensing Technologies in Space Missions

When NASA and the Indian Space Research Organization’s (ISRO) new Earth satellite NISAR (NASA-ISRO Synthetic Aperture Radar) launches in coming months, it will capture images of Earth’s surface so detailed they will show how much small plots of land and ice are moving, down to fractions of an inch. Imaging nearly all of Earth’s solid surfaces twice every 12 days, it will see the flex of Earth’s crust before and after natural disasters such as earthquakes; it will monitor the motion of glaciers and ice sheets; and it will track ecosystem changes, including forest growth and deforestation. The mission’s extraordinary capabilities come from the technique noted in its name: synthetic aperture radar, or SAR. Pioneered by NASA for use in space, SAR combines multiple measurements, taken as a radar flies overhead, to sharpen the scene below. To get such detail without SAR, radar satellites would need antennas too enormous to launch, much less operate. At 39 feet (12 meters) wide when deployed, NISAR’s radar antenna reflector is as wide as a city bus is long. Yet it would have to be 12 miles (19 kilometers) in diameter for the mission’s L-band instrument, using traditional radar techniques, to image pixels of Earth down to 30 feet (10 meters) across. Synthetic aperture radar “allows us to refine things very accurately,” said Charles Elachi, who led NASA spaceborne SAR missions before serving as director of NASA’s Jet Propulsion Laboratory in Southern California from 2001 to 2016. “The NISAR mission will open a whole new realm to learn about our planet as a dynamic system.” One type of SAR-based visualization is an interferogram, a composite of two images taken at separate times that reveals the differences by measuring the change in the delay of echoes. Though they may look like modern art to the untrained eye, the multicolor concentric bands of interferograms show how far land surfaces have moved: The closer the bands, the greater the motion. Seismologists use these visualizations to measure land deformation from earthquakes. Another type of SAR analysis, called polarimetry, measures the vertical or horizontal orientation of return waves relative to that of transmitted signals. Waves bouncing off linear structures like buildings tend to return in the same orientation, while those bouncing off irregular features, like tree canopies, return in another orientation. By mapping the differences and the strength of the return signals, researchers can identify an area’s land cover, which is useful for studying deforestation and flooding. #ISRO #NASA #NISAR NASA’s Jet Propulsion Laboratory used radar data taken by ESA’s Sentinel-1A satellite before and after the 2015 eruption of the Calbuco volcano in Chile to create this interferogram showing land deformation. The color bands west of the volcano indicate land sinking. NISAR will produce similar images. (ESA/NASA/JPL-Caltech)

How to Access Open-Source Hyperspectral Satellite Data Hyperspectral imaging is revolutionizing how we monitor Earth's ecosystems - from detecting subtle plant stress to mapping minerals, pollution, and coastal changes. But where can you actually get this powerful data? I created this one-page visual guide to help researchers, students, and environmental professionals discover free and open-source hyperspectral satellite data and start exploring the invisible spectrum. Key Missions Covered: ~ EnMAP (Germany): Coastal and terrestrial ecosystem monitoring ~ PRISMA (Italy): Earth observation for environmental and agricultural uses ~ HySIS (India): High-resolution spectral analysis ~ DESIS (Germany/USA): Mounted on the ISS, great for land analysis ~ AVIRIS (NASA): Airborne hyperspectral sensor with global datasets ~ Hyperion EO-1 (NASA): Legacy satellite, still valuable archive ~ EMIT (NASA): Focused on mineral dust detection Tools for Processing: Use platforms like SNAP, QGIS, ENVI, and Python libraries (e.g., spectral, rasterio, geemap) to visualize and analyze hyperspectral data. Where to Access the Data: ~ EnMAP - https://lnkd.in/e-KfxGzj ~ PRISMA - https://lnkd.in/eznCNS6G ~ HySIS (ISRO Bhuvan platform) - https://lnkd.in/ejA8Xy3m ~ DESIS via Teledyne Brown - https://lnkd.in/eQpeY2te ~ AVIRIS - https://lnkd.in/edun__ra ~ NASA’s Earthdata portal (Hyperion, EMIT) - https://lnkd.in/eeMGhgAH Hyperspectral data is complex, but the insights it offers are invaluable -especially in environmental monitoring, agriculture, and climate science. This guide is designed to help you get started. Let me know if you’ve used hyperspectral data or are planning to! #HyperspectralImaging #RemoteSensing #Geospatial #EarthObservation #OpenData #ClimateTech #GIS #EnvironmentalScience #ResearchTools #DataScience

ESA’s Biomass mission has just released its first images — and they’re exciting: 🔗 https://lnkd.in/gSYpn9YY These early images showcase the potential of P-band synthetic aperture radar (SAR) to deliver novel insights into forest structure from space. Unlike lidar-based missions like GEDI, which rely on canopy height and allometric models to estimate biomass, SAR measures the radar energy reflected from woody vegetation directly — offering a new way to assess forest carbon stocks. Although the mission targets a 20% uncertainty at the hectare scale, radar has its limits. SAR signals begin to saturate in very dense forests (typically >300 Mg/ha), meaning combining with lidar may give more accurate estimates in primary tropical forests where biomass is high. And novel approaches to reducing relative error below 20% will be needed (go Earthshot!). Regardless, for restoration monitoring, secondary forests, and low-to-moderate biomass regions, BIOMASS could be transformative. The mission is still in its early calibration phase, and first biomass products are expected in about a year or so. In the meantime, we can expect a steady stream of beautiful images — like this first snapshot of northern Amazonia, where dark tones highlight low-biomass areas such as wetlands and floodplains. A big step forward for global carbon monitoring — and a promising complement to lidar missions past and future. #RemoteSensing #ClimateScience #Biomass #Forests #ESA #GEDI #EarthObservation #CarbonMapping

🌊 A NASA instrument designed to map minerals is now helping monitor water quality from space. A recent study showed how EMIT — a hyperspectral imager aboard the ISS — detected signs of sewage in coastal waters off Southern California. EMIT identified pigments linked to harmful cyanobacteria in a wastewater plume from the Tijuana River, complementing traditional water sampling. This innovative use of space technology could help fill critical data gaps and support efforts to protect public health and marine ecosystems. 👉 Learn more about how NASA Earth science is advancing nearshore coastal water quality monitoring! https://lnkd.in/exU8M6xP Christine Lee, K. Dana Chadwick, Keith Gaddis, Kelly Luis

Satellite achieves autonomous decision-making in space using onboard AI in 90 seconds A briefcase-sized satellite successfully used onboard AI to autonomously decide where and when to capture scientific images, completing the entire decision cycle in under 90 seconds without human input. NASA's Jet Propulsion Laboratory tested the "Dynamic Targeting" technology aboard a satellite built by UK startup Open Cosmos, equipped with machine learning processors from Dublin-based Ubotica. The system scans 500 kilometers ahead of the satellite's orbit, captures preview images, and analyzes cloud cover in real-time. Clear skies trigger detailed surface photography, while cloudy conditions prompt the satellite to skip shots entirely. This intelligent filtering saves bandwidth, storage capacity, and processing time while dramatically improving data quality for scientists. Traditional satellites function as passive data collectors, imaging whatever passes beneath them and transmitting everything back to Earth for later analysis. The AI-powered approach enables immediate disaster response capabilities, potentially detecting wildfires, volcanic eruptions, and severe storms within minutes rather than days after post-processing. The breakthrough builds on previous International Space Station demonstrations and represents a fundamental shift toward autonomous space-based intelligence that could transform Earth observation, climate monitoring, and emergency response systems. 🛰️https://lnkd.in/e-b_f-Xw